Quantum Pattern Recognition

I review and expand the model of quantum associative memory that I have recently proposed. In this model binary patterns of n bits are stored in the quantum superposition of the appropriate subset of the computational basis of n qbits. Information can be retrieved by performing an input-dependent rotation of the memory quantum state within this subset and measuring the resulting state. The amplitudes of this rotated memory state are peaked on those stored patterns which are closest in Hamming distance to the input, resulting in a high probability of measuring a memory pattern very similar to it. The accuracy of pattern recall can be tuned by adjusting a parameter playing the role of an effective temperature. This model solves the well-known capacity shortage problem of classical associative memories, providing a large improvement in capacity. PACS: 03.67.-a     

个人信息检索概述

个人数字信息检索技术随着搜索技术的发展而蓬勃兴起,满足了人们对存储在个人电脑中的数据信息的检索需要。讨论了个人信息检索技术的历史、现状,比较了现有的桌面搜索产品,总结了个人信息技术面对的主要问题。在参考其他个人信息检索研究的基础上,针对未开放格式文件的检索问题,提出了个人信息检索模型的改进。     

IE浏览安全的几种方法

介绍用IE上网浏览注意安全的几种方法。     

形态学联想记忆的记忆性能研究

形态学联想记忆在异联想时,在对多个模式对进行记忆之后,逐一对每一个模式对的输入模式进行联想,存在得不到正确的输出模式的情形。对形态学联想记忆在异联想时存在的问题进行研究显得非常的必要,否则,对形态学联想记忆的改进工作就会变得盲目。分析形态学联想记忆的记忆性能,得到几个有意义的结论,通过字符图像的仿真实验,对这些结论进行了验证。     

对数-指数形态学联想记忆

利用对数和指数算子构建了一种新的形态学联想记忆方法,简称LEMAM.理论分析表明:自联想LEMAM(简称ALEMAM)具有无限存储能力、一步回忆记忆、一定的抵抗腐蚀噪声或膨胀噪声的能力,在输入完全或在一定的噪声范围内,能够保证完全回忆记忆;异联想LEMAM(简称HLEMAM)在输入完全情况下,不能保证完全回忆记忆,但当满足一定条件时,也能够达到完美联想记忆.对比实验结果表明:在一些情况下,LEMAM能够取得较好的联想记忆效果.总体来说,LEMAM丰富了形态学联想记忆的理论和实践,可以作为一种神经计算模型加以研究和利用.     

基于αβ运算的多层联想记忆模型的研究

介绍了αβ运算符的定义和αβ联想记忆矩阵的四种操作。通过四种矩阵操作来实现模式对的培训和回忆。αβ多层联想记忆模型相比形态学联想记忆模型数值计算相对容易。最后,通过αβ多层联想记忆的数字模拟实例验证了αβ多层联想记忆具有良好的回忆性能。     

基于用户浏览轨迹的商品推荐

随着电子商务的迅速发展,推荐系统在这些网站中得到了广泛的应用。目前应用最广泛的个性化推荐算法是协同过滤推荐算法,但是该方法存在稀疏矩阵与冷启动问题。根据用户浏览记录推荐商品是缓解这些问题的一个重要研究方向,这些方法根据用户在电子商务网站的访问日志,提取出用户的浏览路径序列,即用户浏览轨迹,为用户推荐偏爱商品。目前,通过分析用户浏览路径为用户推荐商品的方法主要依据用户浏览轨迹模式匹配或者从用户浏览轨迹中商品与下一个商品关系的角度进行考虑。而本研究从浏览轨迹中被浏览商品与最终被购买商品关系的角度出发,并以此为基础建立用户浏览轨迹偏爱模型,挖掘用户偏爱,为用户推荐商品。实验表明,所提方法能够在一定程度上解决因为新用户缺少历史购买及评分记录而引起的新用户冷启动问题,提高了推荐方法的准确度与召回率。     

基于历史信息提升关键字查询效率

关系数据库上的关键字查询使用户不必了解SQL语法或者数据库模式即可方便进行检索,并利用关系表的连接来保证查询的完整性.但是目前已有的关键字查询技术对于每个用户发起的查询皆从底层数据开始处理,而忽略了历史查询信息的使用.历史信息不仅包含了历史查询结果,而且反映了关键字之间的相关性,在查询过程中使用历史信息会提升查询效率.此篇论文正是针对此问题提出了新的解决方案:首先利用划分算法将用户输入的关键字划分为历史关键字和新关键字的组合;利用历史信息展开关键字查询,得到以子图形式存在的查询结果;基于与关键字的相关度对结果子图进行排序.最后,基于DBLP数据集,实验在执行时间和查准率方面证明了算法的有效性和高效性.     

一种高效、可扩展细粒度缓存管理混合存储研究

混合主存储器由DRAM构成,它可用作cache来扩展非易失性存储器,相比传统的主存储器能够提供更大的存储能力。不过,要使混合存储器具有高性能和可扩展性,一个关键的挑战在于需要对缓存在DRAM中的数据的元数据(如标签)以一个细粒度的方式进行有效管理。基于这样的观察:利用DRAM缓存行的局部性,将元数据与元数据对应的数据存储在片外缓存中相同的行,使用一个小的缓冲区来只缓存最近被访问的片内缓存行,以降低细粒度DRAM缓存的开销。利用这种细粒度的DRAM高速缓存的灵活性和效率,还开发了一种自适应的策略来选择在数据迁移到DRAM时最佳的迁移粒度。在搭配了512MB的DRAM缓存的混合型存储系统中,建议使用8kB的片上缓存,这样,相比一个传统的8MB的SRAM元数据存储,即使没有考虑大的SRAM元数据存储的能源开销,也可以提升6%以内的性能,以及18%的能效节约。     

特大图像快速浏览解决方案研究及实现*

如何实现特大图像快速浏览是航测图像应用中的关键问题之一。主要从实现原理、算法流程、快速显示技术三方面讨论了这一问题,给出了以图像动态显示、文件流和双缓冲使用为主要技术的解决方案,介绍了一个特大图像的快速浏览实例系统MONSTERSee。     

COMIB: COMposite Icon Browser for multimedia databases

COMIB(COMposite Icon Browser) is a graphical user interface for retrieval of multimedia databases. It gives users the effect of browsing and navigating multimedia objects simultaneously in a screen using composite icons, that may be thumbnails of the several nested attribute values of those objects. Users can specify these attributes with a mouse while browsing the visualized aggregation hierarchy. Both querying and browsing can be interleaved via query reformulation. We show how these features of COMIB overcome the three drawbacks of the browsing paradigm such as no overview of many objects, the repetitious short-sighted navigation, and the weak presentation of a multimedia object. We also explain the retrieval mechanism algebraically and describe the implementation of COMIB based on this mechanism.     

基于Android平台的校园信息系统的设计与实现

随着移动网络终端特别是Android智能手机的普及,使得越来越多的师生希望通过移动终端来获取信息,该系统针对现有校园移动信息系统的可操作性差、响应较慢、数据流量大等缺点,提出一种基于Android平台的校园信息系统的设计和实现方法,并分析该系统的架构及主要实现技术。该系统的实现对校园移动办公具有一定的实用和参考价值。     

Behavioural study of median associative memory under true-colour image patterns

Median associative memories (MED-AMs) are a special type of associative memory that substitutes the maximum and minimum operators of a morphological associative memory with the median operator. This associative model has been applied to restore grey scale images and provided a better performance than morphological associative memories when the patterns are altered with mixed noise. Despite their power, MED-AMs have not been adopted in problems related with true-colour patterns. In this paper, we describe how MED-AMs can be applied to problems involving true-colour patterns. Furthermore, a complete study of the behaviour of this associative model in the restoration of true-colour images is performed using a benchmark of 16,000 images altered by different noise types.     

Exploiting User Interests to Characterize Navigational Patterns in Web Browsing Assistance

In order to be capable of exploiting context for pro-active information recommendation, agents need to extract and understand user activities based on their knowledge of the user interests. In this paper, we propose a novel approach for context-aware recommendation in browsing assistants based on the integration of user profiles, navigational patterns and contextual elements. In this approach, user profiles built using an unsupervised Web page clustering algorithm are used to characterize user ongoing activities and behavior patterns. Experimental evidence show that using longer-term interests to explain active browsing goals user assistance is effectively enhanced.

Enhancing Web accessibility via the Vox Portal and a Web-hosted dynamic HTMLVoxML converter

Interactive voice browsers offer an alternative paradigm that enables both sighted and visually impaired users to access the World Wide Web. In addition to the desktop PC, voice browsers afford ubiquitous mobile access to the World Wide Web using a wide range of consumer devices. This technology can facilitate a safe, ‘hands-free' browsing environment which is of importance both to car drivers and various mobile and technical professionals. By providing voice-mediated access, information providers can reach a wider audience and leverage existing investment in their World Wide Web content. In this paper we describe the Vox Portal, a scaleable VoxML client, and a World Wide Web Server-hosted dynamic HTMLVoxML converter.     

GOHSE: Ontology driven linking of biology resources

We describe the GOHSE system, an application to support browsing of biology resources. The Conceptual Open Hypermedia Service (COHSE) system enhances web resources through the dynamic addition of hypertext links. These links are derived through the use of an ontology and associated lexicon along with a mapping from concepts to possible link targets. GOHSE applies COHSE to Bioinformatics, using the Gene Ontology (GO) as an ontology and associated keyword mappings and GO associations as link targets. The resulting demonstrator provides both glossary functionality and the possibility of building knowledge based hypertext structures linking bioinformatics resources.     

Let's browse: a collaborative browsing agent

Web browsing, like most of today's desktop applications, is usually a solitary activity. Other forms of media, such as watching television, are often done by groups of people, such as families or friends. What would it be like to do collaborative Web browsing? Could the computer provide assistance to group browsing by trying to help find mutual interests among the participants? Let's Browse is an experiment in building an agent to assist a group of people in browsing, by suggesting new material likely to be of common interest. It is built as an extension to the single user Web browsing agent Letizia. Let's Browse features automatic detection of the presence of users, automated “channel surfing” browsing, and dynamic display of the user profiles and explanation of recommendations.